Prediction of Peak Path of Building Carbon Emissions Based on the STIRPAT Model: A Case Study of Guangzhou City

Xiangyang Jiang () and Shilei Lu
Additional contact information
Xiangyang Jiang: School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
Shilei Lu: School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China

Energies, 2025, vol. 18, issue 7, 1-18

Abstract: Carbon emissions from the building sector have a substantial effect on peak carbon targets. However, there are large differences in the carbon peak paths between different regions and buildings. This study used the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to study the peak carbon emission paths of buildings in Guangzhou City. Through ridge regression and F-tests, the main driving factors affecting carbon emissions from buildings were identified. Finally, the decreasing rate of carbon emissions per unit of building area in Guangzhou was changed to predict the time of the carbon peak. The results of the ridge regression analysis and F-test show that the urbanization rate, total floor area, consumption level of residents, value-added of the tertiary industry, and carbon emissions per unit of public floor area are the main driving factors of the model. The minimum reduction rate of carbon emissions per unit floor area required to achieve a building carbon peak in Guangzhou City by 2030 is 5%. This study provides a theoretical reference for Guangzhou to realize peak building carbon emissions.

Keywords: building carbon emissions; STIRPAT model; ridge regression; F-test; carbon peak (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/7/1633/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/7/1633/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:7:p:1633-:d:1619606

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().